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cognitive_arbitrate_temporal_objectives

Arbitrate short vs long term payoffs using hyperbolic vs exponential discounting and Ulysses pre-commitment contracts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
k_hyperbolicNo
long_term_optionYes
gamma_exponentialNo
short_term_optionYes
audit_action_switchNo
register_commitmentNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

C2.7/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It hints at a theoretical mechanism but does not state whether the tool is read-only, whether it registers commitments or audits switches as side effects, or what observable behavior follows invocation. The presence of register_commitment and audit_action_switch parameters suggests possible write behavior that is left undisclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single efficient sentence with the primary task front-loaded before the method. It wastes no words, though the dense jargon reduces immediate readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a six-parameter tool with no annotations and zero schema description coverage, one sentence is not complete. The agent cannot infer expected input shapes, side effects, commitment behavior, or how the arbitration result is returned. The output schema helps but does not offset the missing guidance.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It gives rough context for short_term_option and long_term_option and vaguely maps 'hyperbolic vs exponential' to k_hyperbolic and gamma_exponential, but it says nothing about audit_action_switch or register_commitment and offers no concrete semantics for the nested objects. This is insufficient for six parameters with zero schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('arbitrate'), a clear resource ('short vs long term payoffs'), and a distinctive method ('hyperbolic vs exponential discounting and Ulysses pre-commitment contracts'). It is specific enough to distinguish the tool's intent from most siblings, though it relies on jargon and does not explicitly contrast with cognitive.arbitrate_temporal_objectives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for temporal trade-off decisions but provides no guidance on when to choose it over alternatives, no preconditions, and no exclusions. With a large sibling list, an agent gets little help selecting this tool correctly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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